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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationMon, 21 Oct 2013 19:08:13 -0400
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2013/Oct/21/t13823970476kb470zvnrb3ore.htm/, Retrieved Mon, 29 Apr 2024 04:18:56 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=217904, Retrieved Mon, 29 Apr 2024 04:18:56 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-     [Boxplot and Trimmed Means] [Care Age 10 Data] [2009-10-26 09:01:50] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   PD  [Boxplot and Trimmed Means] [Care Age 7 Data] [2009-10-26 18:36:29] [98fd0e87c3eb04e0cc2efde01dbafab6]
-   P     [CARE Data - Boxplots and Scatterplot Matrix] [CARE Data] [2010-10-19 14:16:27] [3fdd735c61ad38cbc9b3393dc997cdb7]
- RM        [CARE Data - Boxplots and Scatterplot Matrix] [CARE data - works...] [2011-10-17 10:23:12] [98fd0e87c3eb04e0cc2efde01dbafab6]
- RMP         [Boxplot and Trimmed Means] [CARE Study Age 7 ] [2013-10-17 12:59:45] [34296d8f7657c52ed60d5bff9133afec]
-   PD          [Boxplot and Trimmed Means] [CARE Study- Year ...] [2013-10-21 21:07:34] [74be16979710d4c4e7c6647856088456]
- RMP               [Kendall tau Correlation Matrix] [year 10 data matr...] [2013-10-21 23:08:13] [ea7d2f6236f86857f3b994562beff551] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
74	71	69	67	73
74	71	69	67	73
74	71	69	67	73
74	71	69	67	73
74	71	69	67	73
74	71	69	67	73
75	72	75	69	73
77	72	77	72	74
78	73	79	72	75
79	77	79	73	77
79	77	81	73	77
80	78	81	73	77
80	78	83	73	78
81	79	83	75	79
81	79	83	77	80
82	79	83	78	81
82	80	84	79	81
83	80	84	80	82
83	80	84	80	82
84	80	84	81	82
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85	81	84	82	82
85	81	85	83	82
85	82	85	83	83
86	82	85	83	83
86	82	86	84	83
86	82	86	84	83
87	82	86	84	83
88	82	86	84	83
88	84	86	84	84
88	84	86	84	84
88	85	86	84	84
88	86	87	84	84
88	86	87	85	84
88	86	87	86	85
89	86	87	86	86
89	86	87	87	86
89	86	87	87	86
89	86	88	87	86
90	86	88	87	87
90	87	88	88	88
91	88	88	88	88
91	88	88	88	88
91	88	88	89	89
91	88	88	89	89
91	89	88	89	89
91	89	88	89	89
91	89	88	89	89
91	90	89	89	89
91	90	89	89	90
92	90	90	90	90
92	91	90	90	90
92	91	90	90	90
93	91	91	90	90
93	91	91	90	91
94	91	91	90	91
94	92	92	90	91
94	92	92	91	92
94	92	92	91	92
95	92	92	91	92
95	92	93	92	92
95	92	93	92	92
95	92	93	94	92
96	92	93	94	92
96	93	93	94	93
97	94	94	94	93
97	94	94	94	93
97	95	94	94	93
97	95	94	95	93
97	95	95	95	93
98	95	95	96	94
98	95	95	96	94
98	96	95	96	94
98	96	95	96	95
98	96	96	96	95
98	97	97	97	96
98	97	97	97	96
98	97	99	98	96
100	98	100	98	97
100	98	101	98	97
100	99	101	100	97
102	100	101	100	98
102	100	102	101	98
102	100	102	102	98
102	102	102	103	98
102	103	102	104	99
103	103	103	105	99
103	103	103	105	100
104	104	103	105	100
104	105	104	105	100
106	105	104	105	100
106	105	105	106	101
106	105	105	106	102
107	105	105	107	104
108	108	105	107	104
112	109	105	107	105
112	111	105	110	107
113	112	108	110	107
114	112	113	111	107
114	112	113	111	107
114	112	113	111	107
114	112	113	111	107
114	112	113	111	107
114	112	113	111	NA

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Herman Ole Andreas Wold' @ wold.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=217904&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Herman Ole Andreas Wold' @ wold.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=217904&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=217904&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Herman Ole Andreas Wold' @ wold.wessa.net






Correlations for all pairs of data series (method=pearson)
WJ10AFSWJ10AVAWJ10ARDWJ10AMAWJ10AKN
WJ10AFS10.9950.9840.9910.995
WJ10AVA0.99510.9830.9910.996
WJ10ARD0.9840.98310.9830.979
WJ10AMA0.9910.9910.98310.993
WJ10AKN0.9950.9960.9790.9931

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & WJ10AFS & WJ10AVA & WJ10ARD & WJ10AMA & WJ10AKN \tabularnewline
WJ10AFS & 1 & 0.995 & 0.984 & 0.991 & 0.995 \tabularnewline
WJ10AVA & 0.995 & 1 & 0.983 & 0.991 & 0.996 \tabularnewline
WJ10ARD & 0.984 & 0.983 & 1 & 0.983 & 0.979 \tabularnewline
WJ10AMA & 0.991 & 0.991 & 0.983 & 1 & 0.993 \tabularnewline
WJ10AKN & 0.995 & 0.996 & 0.979 & 0.993 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=217904&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]WJ10AFS[/C][C]WJ10AVA[/C][C]WJ10ARD[/C][C]WJ10AMA[/C][C]WJ10AKN[/C][/ROW]
[ROW][C]WJ10AFS[/C][C]1[/C][C]0.995[/C][C]0.984[/C][C]0.991[/C][C]0.995[/C][/ROW]
[ROW][C]WJ10AVA[/C][C]0.995[/C][C]1[/C][C]0.983[/C][C]0.991[/C][C]0.996[/C][/ROW]
[ROW][C]WJ10ARD[/C][C]0.984[/C][C]0.983[/C][C]1[/C][C]0.983[/C][C]0.979[/C][/ROW]
[ROW][C]WJ10AMA[/C][C]0.991[/C][C]0.991[/C][C]0.983[/C][C]1[/C][C]0.993[/C][/ROW]
[ROW][C]WJ10AKN[/C][C]0.995[/C][C]0.996[/C][C]0.979[/C][C]0.993[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=217904&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=217904&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=pearson)
WJ10AFSWJ10AVAWJ10ARDWJ10AMAWJ10AKN
WJ10AFS10.9950.9840.9910.995
WJ10AVA0.99510.9830.9910.996
WJ10ARD0.9840.98310.9830.979
WJ10AMA0.9910.9910.98310.993
WJ10AKN0.9950.9960.9790.9931






Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
WJ10AFS;WJ10AVA0.99550.99790.9825
p-value(0)(0)(0)
WJ10AFS;WJ10ARD0.9840.99780.9827
p-value(0)(0)(0)
WJ10AFS;WJ10AMA0.99140.99830.9846
p-value(0)(0)(0)
WJ10AFS;WJ10AKN0.99480.99830.985
p-value(0)(0)(0)
WJ10AVA;WJ10ARD0.98290.99790.9828
p-value(0)(0)(0)
WJ10AVA;WJ10AMA0.99090.99780.9816
p-value(0)(0)(0)
WJ10AVA;WJ10AKN0.99560.99850.9858
p-value(0)(0)(0)
WJ10ARD;WJ10AMA0.98310.99810.984
p-value(0)(0)(0)
WJ10ARD;WJ10AKN0.97910.99760.9805
p-value(0)(0)(0)
WJ10AMA;WJ10AKN0.9930.99830.985
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
WJ10AFS;WJ10AVA & 0.9955 & 0.9979 & 0.9825 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10AFS;WJ10ARD & 0.984 & 0.9978 & 0.9827 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10AFS;WJ10AMA & 0.9914 & 0.9983 & 0.9846 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10AFS;WJ10AKN & 0.9948 & 0.9983 & 0.985 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10AVA;WJ10ARD & 0.9829 & 0.9979 & 0.9828 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10AVA;WJ10AMA & 0.9909 & 0.9978 & 0.9816 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10AVA;WJ10AKN & 0.9956 & 0.9985 & 0.9858 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10ARD;WJ10AMA & 0.9831 & 0.9981 & 0.984 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10ARD;WJ10AKN & 0.9791 & 0.9976 & 0.9805 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
WJ10AMA;WJ10AKN & 0.993 & 0.9983 & 0.985 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=217904&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]WJ10AFS;WJ10AVA[/C][C]0.9955[/C][C]0.9979[/C][C]0.9825[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10AFS;WJ10ARD[/C][C]0.984[/C][C]0.9978[/C][C]0.9827[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10AFS;WJ10AMA[/C][C]0.9914[/C][C]0.9983[/C][C]0.9846[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10AFS;WJ10AKN[/C][C]0.9948[/C][C]0.9983[/C][C]0.985[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10AVA;WJ10ARD[/C][C]0.9829[/C][C]0.9979[/C][C]0.9828[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10AVA;WJ10AMA[/C][C]0.9909[/C][C]0.9978[/C][C]0.9816[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10AVA;WJ10AKN[/C][C]0.9956[/C][C]0.9985[/C][C]0.9858[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10ARD;WJ10AMA[/C][C]0.9831[/C][C]0.9981[/C][C]0.984[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10ARD;WJ10AKN[/C][C]0.9791[/C][C]0.9976[/C][C]0.9805[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[ROW][C]WJ10AMA;WJ10AKN[/C][C]0.993[/C][C]0.9983[/C][C]0.985[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=217904&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=217904&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
WJ10AFS;WJ10AVA0.99550.99790.9825
p-value(0)(0)(0)
WJ10AFS;WJ10ARD0.9840.99780.9827
p-value(0)(0)(0)
WJ10AFS;WJ10AMA0.99140.99830.9846
p-value(0)(0)(0)
WJ10AFS;WJ10AKN0.99480.99830.985
p-value(0)(0)(0)
WJ10AVA;WJ10ARD0.98290.99790.9828
p-value(0)(0)(0)
WJ10AVA;WJ10AMA0.99090.99780.9816
p-value(0)(0)(0)
WJ10AVA;WJ10AKN0.99560.99850.9858
p-value(0)(0)(0)
WJ10ARD;WJ10AMA0.98310.99810.984
p-value(0)(0)(0)
WJ10ARD;WJ10AKN0.97910.99760.9805
p-value(0)(0)(0)
WJ10AMA;WJ10AKN0.9930.99830.985
p-value(0)(0)(0)






Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01111
0.02111
0.03111
0.04111
0.05111
0.06111
0.07111
0.08111
0.09111
0.1111

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Correlation Tests \tabularnewline
Number of significant by total number of Correlations \tabularnewline
Type I error & Pearson r & Spearman rho & Kendall tau \tabularnewline
0.01 & 1 & 1 & 1 \tabularnewline
0.02 & 1 & 1 & 1 \tabularnewline
0.03 & 1 & 1 & 1 \tabularnewline
0.04 & 1 & 1 & 1 \tabularnewline
0.05 & 1 & 1 & 1 \tabularnewline
0.06 & 1 & 1 & 1 \tabularnewline
0.07 & 1 & 1 & 1 \tabularnewline
0.08 & 1 & 1 & 1 \tabularnewline
0.09 & 1 & 1 & 1 \tabularnewline
0.1 & 1 & 1 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=217904&T=3

[TABLE]
[ROW][C]Meta Analysis of Correlation Tests[/C][/ROW]
[ROW][C]Number of significant by total number of Correlations[/C][/ROW]
[ROW][C]Type I error[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]0.01[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.02[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.03[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.04[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.05[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.06[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.07[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.08[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.09[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.1[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=217904&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=217904&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01111
0.02111
0.03111
0.04111
0.05111
0.06111
0.07111
0.08111
0.09111
0.1111


Figures (Output of Computation)

Input Parameters & R Code

Parameters (Session):
Parameters (R input):
par1 = pearson ;
R code (references can be found in the software module):
panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
ncorrs <- (n*n -n)/2
mycorrs <- array(0, dim=c(10,3))
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
for (iii in 1:10) {
iiid100 <- iii / 100
if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1
if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1
if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1
}
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
for (iii in 1:10) {
iiid100 <- iii / 100
a<-table.row.start(a)
a<-table.element(a,round(iiid100,2),header=T)
a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')